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We are very pleased to introduce the Proceedings of the Seventh International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI'15). This is the premier forum for user interface (UI) research in the automotive domain. As with previous conferences, the papers and presentations as part of AutomotiveUI'15 addresses novel invehicle services, models of and concepts for enhancing the driver experience, driver performance and behavior, development of semi and fully autonomous driving, and the needs of different user groups.
It is widely recognized that the automobile is progressing towards the status of "computer on wheels" with greater connectivity to the outside world and higher levels of autonomy. As a consequence, not only will what we consider to be "driving" fundamentally change, but also a plethora of novel functions and services will become available to the users of future vehicles. The design of the automotive user-interface is/will be complex, dependent on many 'hard' (e.g. performance, safety) and 'soft' (e.g. likes/ dislikes) variables. The papers within this year's Automotive UI conference reflect this breadth and depth of issues, ranging from specific usercentred issues facing industry now (e.g. relating to evaluation of distraction), through to longerterm perspectives, such as how to design UIs for car interiors in which the "driver" spends large amounts of time not in control of his/her vehicle.
Automotive UI'15 is hosted by the Human Factors Research Group (HFRG), Faculty of Engineering at the University of Nottingham. The group conducts research into the human factors (ergonomics) issues for new technology, across a range of domains including transport (road and rail), healthcare, manufacturing, education, etc. Specific to this conference, HFRG investigates the user-interface design and evaluation issues for future vehicles, often using simulation as a safe, controlled and cost-effective environment.
Proceeding Downloads
Intelligent in-vehicle touchscreen aware of the user intent for reducing distractions: a pilot study
Intent-aware displays aim to simplify and expedite the task of selecting an icon displayed on an in-vehicle touchscreen via a free hand pointing gesture, thus, minimise the incurred effort and/or distractions. This is achieved by determining the user ...
Anthropomorphic agents, transparent automation and driver personality: towards an integrative multi-level model of determinants for effective driver-vehicle cooperation in highly automated vehicles
This paper introduces a model integrating research on antecedents of safe and enjoyable interaction with highly automated advanced driver assistance systems (ADAS). It focuses on the psychological processes during the initial encounters with a system, ...
User interface considerations to prevent self-driving carsickness
Self-driving cars have the potential to bring significant benefits to drivers and society at large. However, all envisaged scenarios are predicted to increase the risk of motion sickness. This will negatively affect user acceptance and uptake and hence ...
Comparing heart rate and pupil size as objective measures of workload in the driving context: initial look
Historically detection of workload has been done through the use of subjective measures but new demands in research are driving interests to objective and immediate physiological measures. This paper is a look at some initial data from a study comparing ...
Stick'n conversation: stick in-car conversation into places using multi person finger pointing gestures
In-car conversations are transient and cannot be shared with others. We propose a method to stick in-car conversation into places by the recognition of multiple peoples' finger pointing gestures. We use a motion capture device to detect finger pointing ...
TactiCar: towards supporting drivers during lane change using vibro-tactile patterns
While deciding if it is possible to overtake a slower car, drivers have to take several factors into account. Accident statistics show that many drivers make mistakes in this sit-uation. We want to assist drivers during lane change deci-sion without ...
Estimation of drivers' emotional states based on neuroergonmic equipment: an exploratory study using fNIRS
Research has shown the negative effects of emotions on driving performance and safety, whereas a small number of neuroimaging studies has been conducted to investigate a driver's brain activities while driving with emotions. This study aims to explore ...
Ghost driver: a platform for investigating interactions between pedestrians and driverless vehicles
How will pedestrians and cyclists interact with self-driving cars when there is no human driver? To find answers to this question we need a secure experimental design in which pedestrians can interact with a car that appears to drive on its own. In ...
"Don't make me turn this seat around!": driver and passenger activities and positions in autonomous cars
From the earliest concepts of autonomous cars, a prototypical model has emerged in which occupants freely orient themselves to engage in non-driving activities. This new environment prompts questions about how car occupants will actually sit, what ...
Advanced traffic light interface: countdown timers to increase user experience
Based on existing LED traffic light interfaces, this paper evaluates the possibilities of increasing user experience for car drivers by displaying the remaining time of a red phase. Fifteen design approaches were conceived and im-plemented. Five of them ...
Reducing driving violations by receiving feedback from other drivers
The road environment can be seen as a social situation and road user safety can be viewed as not just skills-based and rule-governed. Numerous studies show that intentional driving violations make an independent significant contribution to traffic ...
Design of driver-vehicle interface to reduce mode confusion for adaptive cruise control systems
Adaptive cruise control (ACC) systems have several operational modes. Drivers may be unaware of the mode where they are operating, which can cause traffic crashes. To suppress mode confusion, we developed a new interface design methodology in which the ...
LED-A-pillars: displaying distance information on the cars chassis
As the chassis of cars become more robust, the pillars of a car become broader in order to increase driver safety. As A-pillars grow wider, so too does their negative affect on the panoramic view of the driver and with a smaller field of vision, the ...
Adaptive digital sunshade: blocking the sun from blinding the driver
Bright sunlight impairing the vision of a vehicle's driver is a problem every driver faces regularly. This paper describes an approach of how to solve this particular issue. Our goal is to design a system which reduces the blinding effects of bright ...
Highly automated truck driving: how can drivers safely perform sport exercises on the go?
Highly automated driving enables the driver to engage in activities other than the actual primary driving task. How can truck drivers use phases of highly automated driving meaningfully? Research in the domain of long-distance road haulage shows that ...
Concept of a reference architecture for an extendable in-vehicle adaptive recommendation service
An adaptive recommendation service can reduce driver distraction through reducing the amount of operation steps needed to call a function. It learns the routine user behavior of the driver related to a situation and supports the driver with this ...
On-wheel finger gesture control for in-vehicle systems on central consoles
To reduce visual and biomechanical distractions when drivers interact with in-vehicle systems of the central console, we propose a new driver interface approach that integrates on-wheel gesture control and head-up display. We then verify its ...
Good vibrations: driving with a haptic pedal
The study at hand evaluates if and how perception of haptic pulse feedback provided by an accelerator pedal in a stationary car differs dependent on the shoe type (herein safety boots and plimsolls) or the age and gender of the participant. Intermediate ...
Field studies to investigate safety distance violation with a low-cost observation system
Statistics show that safety distance violation is a major cause of traffic accidents with reasons including high vol-ume of traffic, aggressive driving, inattention/distraction and, in particular, an underestimation of braking distances at certain ...
Deriving future user experiences in autonomous vehicle
Autonomous vehicle will change the user behavior completely; therefore, needs for exploring the user's future experience in the autonomous environment are required. The objective of our study is to explore the direction of design of autonomous vehicle ...
eMotion: retrospective in-car user experience evaluation
- Evangelos Niforatos,
- Evangelos Karapanos,
- Marc Langheinrich,
- Daniela Wurhofer,
- Alina Krischkowsky,
- Marianna Obrist,
- Manfred Tscheligi
Well-established self-reporting methods in HCI such as the Experience Sampling Method (ESM) prove rather limited for sampling in-car experiences, as they distract the driver from the primary task of driving. In this work we present eMotion, a mobile ...
LCTNav: a method for investigating collaborative navigation
- Sandra Trösterer,
- Martin Wuchse,
- Axel Baumgartner,
- Bernhard Maurer,
- Magdalena Gärtner,
- Alexander Meschtscherjakov,
- Manfred Tscheligi
Front-seat passengers can support drivers in navigational tasks, e.g., by giving instructions where to drive. Investigating the success of such collaborative navigation in the driving simulator is a challenge, as suitable navigation tasks are needed. ...
Evaluation of historical electric vehicle (EV) driving data to suggest improvements in driving efficiency
Increasing the operating distance (range) and, in particular, the accuracy of charge state/remaining range displays is very important for battery electrical vehicles (BEVs) to gain market penetration and satisfy customers. Battery drain of BEVs is ...
MaDSAV: maintaining driving skills in semi-autonomous vehicles
- Alexander Meschtscherjakov,
- Rod McCall,
- Nicolas Louveton,
- Thomas Engel,
- Manfred Tscheligi,
- Vincent Koenig
In the future autonomous vehicles will drive on our roads. It is unlikely that we will immediately move from manual to fully autonomous vehicles, instead the mix will change over time and include a large number of semi-autonomous vehicles. As a result ...
An on-road study involving two vehicles: observed differences between an auditory and haptic lane departure warning system
This research examined, as an exploratory secondary analysis, the frequency of lane departure warnings in two commercially available vehicles and users' behavioral and physiological responses to the alarms. The two lane departure systems used different ...
Influence of in-vehicle displays on driver behaviour
- Peter Burns,
- Leanna Belluz,
- Marc Belzile,
- Vittoria Battista,
- Samuel Pedroso,
- James Knowles,
- Vijay Gill,
- Charles Crispim
In-Vehicle Displays (IVDs) have the potential to reduce fuel consumption rates (FCR), thus reducing emissions from in-use vehicles. This project is one of the first to simultaneously explore the impact of IVDs and driver training on both fuel ...
Simulator telemetry (STING) and head up display designer middleware for the NADS MiniSim driving simulator
In-vehicle systems, from infotainment to head up displays, increasingly make use of telemetry data obtained from the vehicle (e.g., speed, location, brake pedal state). Researchers must carefully study the design and use of these dynamic systems to ...
DAZE: a real-time situation awareness measurement tool for driving
A driver's situation awareness (SA) while on the road is a critical factor in his or her ability to make decisions to avoid hazards, plan routes and maintain safe travel. Understanding SA can therefore be a great help when designing or evaluating new ...
Index Terms
- Adjunct Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Recommendations
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
AutomotiveUI '19 | 119 | 34 | 29% |
AutomotiveUI '17 | 85 | 29 | 34% |
AutomotiveUI '17 | 51 | 31 | 61% |
Automotive'UI 16 | 85 | 39 | 46% |
AutomotiveUI '15 | 80 | 38 | 48% |
AutomotiveUI '14 | 79 | 36 | 46% |
AutomotiveUI '13 | 67 | 41 | 61% |
Overall | 566 | 248 | 44% |